ECTRIMS eLearning

Validation of a clinical risk score for long-term progression of MS
ECTRIMS Learn. Aurenção J. 10/25/17; 199421; EP1400
Juliana Calvet Kallenbach Aurenção
Juliana Calvet Kallenbach Aurenção
Contributions
Abstract

Abstract: EP1400

Type: ePoster

Abstract Category: Clinical aspects of MS - 8 Clinical assessment tools

Introduction: Reducing risk of multiple sclerosis (MS) progression is a challenge in the MS treatment. The application of the clinical risk score to predict long term progression is useful and has been little explored.
Objective: To validate a clinical risk score (CRS) for long-term severity based on demographic and clinical factors present in the disease onset.
Methods: CRS-MS was derivate based on five factors identified as more significant after a Cox regression model analysis in 150 patients with ten or more years of the disease. African ancestry, age onset above 30 years, two or more relapses at first year of the disease, pyramidal and cerebellar impairment as first manifestation, and to have EDDSS 3 before the first treatment were identified as independent variables that influence the time to reach progression. The numerical value of 1.0 was given to all factors because hazard ratios (HR) and beta coefficients had close values. The sum of the single scores gives the overall risk score. In the second phase, we validated the score: The CRS-MS was applied in another 270 patients with at least two years of the disease duration.
Results: Progression was observed in 21% (57/270), with mean disease duration of 19,07 years (4-47; SD+- 10,6 years). Among these patients, 66% percent had three or more clinical risk factors and the risk for progression was 14.3 (95% CI 7.2-28.4, p < 0.001). All patients with none factor were progression free.
Conclusion: The CRS-MS was able to predict the risk of long-term progression to patients with two or more years of disease, and it can assist in the choice of an early treatment and individualized to avoid long-term disability.
Disclosure: nothing to disclose

Abstract: EP1400

Type: ePoster

Abstract Category: Clinical aspects of MS - 8 Clinical assessment tools

Introduction: Reducing risk of multiple sclerosis (MS) progression is a challenge in the MS treatment. The application of the clinical risk score to predict long term progression is useful and has been little explored.
Objective: To validate a clinical risk score (CRS) for long-term severity based on demographic and clinical factors present in the disease onset.
Methods: CRS-MS was derivate based on five factors identified as more significant after a Cox regression model analysis in 150 patients with ten or more years of the disease. African ancestry, age onset above 30 years, two or more relapses at first year of the disease, pyramidal and cerebellar impairment as first manifestation, and to have EDDSS 3 before the first treatment were identified as independent variables that influence the time to reach progression. The numerical value of 1.0 was given to all factors because hazard ratios (HR) and beta coefficients had close values. The sum of the single scores gives the overall risk score. In the second phase, we validated the score: The CRS-MS was applied in another 270 patients with at least two years of the disease duration.
Results: Progression was observed in 21% (57/270), with mean disease duration of 19,07 years (4-47; SD+- 10,6 years). Among these patients, 66% percent had three or more clinical risk factors and the risk for progression was 14.3 (95% CI 7.2-28.4, p < 0.001). All patients with none factor were progression free.
Conclusion: The CRS-MS was able to predict the risk of long-term progression to patients with two or more years of disease, and it can assist in the choice of an early treatment and individualized to avoid long-term disability.
Disclosure: nothing to disclose

By clicking “Accept Terms & all Cookies” or by continuing to browse, you agree to the storing of third-party cookies on your device to enhance your user experience and agree to the user terms and conditions of this learning management system (LMS).

Cookie Settings
Accept Terms & all Cookies